datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
audio-reasoning-qa-post-public
audio-reasoning-qa-post-public
Question-answering and multi-task audio reasoning annotations across 15 public audio QA datasets. Spans general audio QA (Clotho-AQA, HeySQuAD), music reasoning (MU-LLaMA, MusicBench, LLARK-MTAT, Music-AVQA), speech-grounded QA (LibriSQA, GigaSpeech), and NVIDIA-aggregator skill subsets (TemporalQA, CountingQA, AudioSet-Speech-QA, GigaSpeech-Long-QA). Closes a substantial slice of the public audio-reasoning SFT gap (compare to NVIDIA AudioSkills-XL… See the full description on the dataset page: https://huggingface.co/datasets/vhands/audio-reasoning-qa-post-public.gemma-4-e4b-audio-qa
Gemma-4 E4B Audio-QA Training Mix
A 91k-row audio question-answering dataset assembled from four public upstream
datasets, formatted as ChatML-style conversations for instruction-tuning an
audio-language model. This is the exact training data used for
bnovikov/gemma-4-e4b-audio-v3.
Important: this repository contains only the metadata and prompts/answers.
The audio files are NOT hosted here. Each audio_path is a source-tagged ID
like librispeech/3664-11714-0019.wav — the prefix… See the full description on the dataset page: https://huggingface.co/datasets/bnovikov/gemma-4-e4b-audio-qa.Beyond-Binary-Instrument-QA
🎵 Beyond Binary Instrument QA:Probing Instrument Grounding in Music Audio-Language Models
Yujun Lee · Joonhyeok Shin · Hyoeun Kim · Kyuhong Shim
Sungkyunkwan University
📄 arXiv
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🤗 Dataset
Benchmark release. Five complementary evaluation configurations test instrument presence, reduced genre-prior reliance, fine-grained discrimination, long-context multi-label recognition, and temporal localization. The release contains 15… See the full description on the dataset page: https://huggingface.co/datasets/leeyujun/Beyond-Binary-Instrument-QA.